Dynatrace announced that the Sustainable Digital Infrastructure Alliance (SDIA) has certified the Dynatrace Cost & Carbon Optimization app.
The certification focused on Dynatrace’s accuracy and transparency in calculating greenhouse gas (GHG) emissions for Amazon Web Services (AWS), Microsoft Azure, Google Cloud Platform (GCP), and on-premises host instances. SDIA’s certification supports the effectiveness and reliability of the Dynatrace Cost & Carbon Optimization app and demonstrates how Dynatrace can help customers achieve their sustainability goals. The SDIA report can be accessed here.
The Cost & Carbon Optimization app delivers real-time insights into the costs and carbon footprint of an organization’s hybrid and multicloud ecosystem, offering optimization recommendations detailing how to reduce both costs and environmental impact. Today, more than 25% of all hosts monitored by Dynatrace OneAgent are reporting their carbon footprint to the Cost & Carbon Optimization app, highlighting the broad interest in IT carbon emissions awareness and reduction.
Max Schulze, CEO at SDIA, said, "SDIA concludes that the Dynatrace Cost and Carbon Optimization app is a reliable estimation system for calculating the operational GHG emissions of IT infrastructure in cloud and on-premises environments. The calculations and methodology used are in line with the best available scientific approach, meeting relevant reporting requirements. Dynatrace meets our requirements for transparency, enabling customers to understand the calculations and to recreate the results for independent verification."
"Understanding and minimizing environmental impact is a critical component of organizations’ strategies as they work to meet the needs and expectations of their customers, employees, investors, and the communities in which they operate,” said Steve Tack, Chief Product Officer, Dynatrace. “SDIA’s certification demonstrates Dynatrace’s continued focus on reducing our collective environmental impact and helping our customers – the largest leading enterprises around the world – to meet their sustainability goals.”
The Dynatrace Cost & Carbon Optimization app is available now.
The Latest
I've spent a lot of time in the channel, and one thing I keep coming back to is this: a partner program is only as good as what it looks like in the field. Many programs look great on paper, but when a partner is in front of a customer navigating a complex hybrid environment or trying to make the case for AI-powered observability, the gap between what a vendor promises and what it actually delivers becomes very clear, very fast ...
Enterprises today operate in a real-time environment where uninterrupted access to trusted data has become a baseline expectation for users, applications and automated systems. Traditional DataOps models, built on manual effort and human triage, cannot keep pace with this always active demand. AI agents are emerging as the operational backbone, ensuring consistent data availability, reinforcing trustworthiness and enabling a level of scale that manual processes cannot achieve ...
For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...
Cloud migration was supposed to be a one-way door. For most enterprises, it turns out it isn't. Cloud data repatriation is a real and growing trend. A new survey ... finds that 89% of organizations plan to expand their on-premises infrastructure footprint over the next two years — and 75% have already moved at least some workloads back from public cloud in the past 24 months. The findings point to a broad rethinking of where data belongs ...
Over the past few years, large language models (LLMs) have revolutionized the software industry. Given their ability to excel at multi-step reasoning, LLMs have helped enterprises streamline workflows and adapt to the unknown. However, employing such models comes with sky-high costs, latency issues, and limited flexibility. In the realm of IT operations, it is generally wiser to employ smaller, domain-specific models instead ...
For years, DevOps teams operated under a simple assumption: collect enough telemetry, and you can find and fix any problem. That assumption is breaking down. Modern enterprises now operate across microservices, hybrid cloud environments, APIs, Kubernetes, and highly automated delivery pipelines. Releases happen continuously, dependencies shift constantly, and failures spread faster than teams can diagnose them ...
New Relic surveyed IT and engineering leaders from the media and entertainment (M&E) sector to understand what's working — and where challenges persist with their observability practices. The findings reveal how M&E organizations are navigating rising platform complexity, audience expectations, and AI-driven change. Below are five takeaways that stand out ...
Let me start with something I've seen play out more times than I can count. A team hits a wall with the cloud. Costs creep up, then spike. Performance starts to feel inconsistent. Someone in finance asks a simple question like "why did this double?" and nobody has a clean answer ... Maybe this isn't the right place for everything. That realization feels like a breakthrough, like you've identified the problem. In reality, you've just identified the starting line ...
In MEAN TIME TO INSIGHT Episode 24, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network observability tool sprawl ...
In cloud-native systems, scaling is often as simple as moving a slider. For on-premise databases, the stakes are different. Over-provisioning hardware is expensive. Under-provisioning leads to performance bottlenecks that are difficult to fix once the equipment is in the rack ...